The rapid growth of cryptocurrency and airdrops in the Web3 ecosystem has provided hackers with new attack vectors. This project assesses the legitimacy of ongoing and upcoming airdrops to distinguish between genuine opportunities and scams, enhancing user safety and trust.
Project Deliverables/Outcomes/Impact:
Delivered a Web app that features ML-based scam probability evaluation, LLM-based sentiment analysis, and threat intel-based URL scanning results
Academic article “Airguard for Detection of Airdrop Scams in Web3” was submitted to peer-reviewed journal IEEE Electronics
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